{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EjoQppiBkoXQ",
        "outputId": "fb689d13-7b2a-4dc8-c791-55efb1d88359"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[Errno 2] No such file or directory: '/content/drive/MyDrive/0.CV/0.Planogram_Compliance/'\n",
            "/home/abhi/streamlit-app\n",
            "/home/abhi/streamlit-app/yolov5\n"
          ]
        }
      ],
      "source": [
        "%cd /content/drive/MyDrive/0.CV/0.Planogram_Compliance/\n",
        "# !git clone https://github.com/ultralytics/yolov5  # clone repo\n",
        "%cd yolov5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 459
        },
        "id": "x9Nq2LchpPTK",
        "outputId": "06f052c3-5d31-4595-f3d9-955ab493a543"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[K     |████████████████████████████████| 3.1 MB 10.5 MB/s \n",
            "\u001b[K     |████████████████████████████████| 596 kB 70.2 MB/s \n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (1.1.5)\n",
            "Collecting pandas\n",
            "  Downloading pandas-1.3.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 11.3 MB 14.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas) (1.19.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas) (2018.9)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas) (1.15.0)\n",
            "Installing collected packages: pandas\n",
            "  Attempting uninstall: pandas\n",
            "    Found existing installation: pandas 1.1.5\n",
            "    Uninstalling pandas-1.1.5:\n",
            "      Successfully uninstalled pandas-1.1.5\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires pandas~=1.1.0; python_version >= \"3.0\", but you have pandas 1.3.4 which is incompatible.\u001b[0m\n",
            "Successfully installed pandas-1.3.4\n"
          ]
        },
        {
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "pandas"
                ]
              }
            }
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Setup complete. Using torch 1.9.0+cu111 (CPU)\n"
          ]
        }
      ],
      "source": [
        "\n",
        "%pip install -q -r requirements.txt  # install dependencies\n",
        "!pip install --upgrade pandas \n",
        "import torch\n",
        "from IPython.display import Image, clear_output  # to display images\n",
        "\n",
        "# clear_output()\n",
        "print(f\"Setup complete. Using torch {torch.__version__} ({torch.cuda.get_device_properties(0).name if torch.cuda.is_available() else 'CPU'})\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "JYs-UOJRpRmc"
      },
      "outputs": [],
      "source": [
        "names = ['Bottle,100PLUS ACTIVE 1.5L','Bottle,100PLUS ACTIVE 500ML','Bottle,100PLUS LEMON LIME 1.5L',\n",
        " 'Bottle,100PLUS ORANGE 500ML', 'Bottle,100PLUS ORIGINAL 1.5L',\n",
        " 'Bottle,100PLUS TANGY ORANGE 1.5L','Bottle,100PLUS ZERO 1.5L', 'Bottle,100PLUS ZERO 500ML','Packet,F:M MAGNOLIA CHOC 1L',\n",
        " 'Bottle,F&N GINGER ADE 1.5L','Bottle,F&N GRAPE 1.5L','Bottle,F&N ICE CREAM SODA 1.5L','Bottle,F&N LYCHEE PEAR 1.5L','Bottle,F&N ORANGE 1.5L',\n",
        " 'Bottle,F&N PINEAPPLE PET 1.5L','Bottle,F&N SARSI 1.5L','Bottle,F&N SS ICE LEM TEA RS 500ML','Bottle,F&N SS ICE LEMON TEA RS 1.5L','Bottle,F&N SS ICE LEMON TEA 1.5L','Bottle,F&N SS ICE LEMON TEA 500ML',\n",
        " 'Bottle,F&N SS ICE PEACH TEA 1.5L','Bottle,SS ICE LEMON GT 1.48L','Bottle,SS WHITE CHRYS TEA 1.48L','Packet,FARMHOUSE FRESH MILK 1L FNDM','Packet,FARMHOUSE PLAIN LF 1L',\n",
        " 'Packet,PURA FRESH MILK 1L FS','Packet,NUTRISOY REG NO SUGAR ADDED 1L','Packet,NUTRISOY PLAIN 475ML','Packet,NUTRISOY PLAIN 1L','Packet,NUTRISOY OMEGA RD SUGAR 1L','Packet,NUTRISOY OMEGA NSA 1L',\n",
        " 'Packet,NUTRISOY ALMOND 1L','Packet,MAGNOLIA FRESH MILK 1L FNDM','Packet,FM MAG FC PLAIN 200ML', 'Packet,MAG OMEGA PLUS PLAIN 200ML','Packet,MAG KURMA MILK 500ML','Packet,MAG KURMA MILK 1L',\n",
        " 'Packet,MAG CHOCOLATE FC 500ML','Packet,MAG BROWN SUGAR SS MILK 1L','Packet,FM MAG LFHC PLN 500ML','Packet,FM MAG LFHC OAT 500ML','Packet,FM MAG LFHC OAT 1L','Packet,FM MAG FC PLAIN 500ML',\n",
        " 'Void,PARTIAL VOID', 'Void,FULL VOID','Bottle,F&N SS ICE LEM TEA 500ML'] "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66,
          "referenced_widgets": [
            "a8dfc2d9adab46608f0422590088f8bc",
            "9286c3e33f314f9fa2e75637407012c8",
            "0f06129bddec41a7be33e144cae60d5f",
            "bac13c2933be4d9bb5e0f79c31ed7e58",
            "42aa0bc9718d475392d0895c4f89adb7",
            "0e12290d551e46f0aa5cef2ea5dcea14",
            "0a089e15424f472aad367262c5462b25",
            "cbeee699e87f487680e9b5f24fb62c74",
            "4b494149de3a4469b6c4b7c9b71e4ed5",
            "4aec28eedbc14a4990b2bdcee3455fca",
            "db8106f763604261bdb732f2edae27c5"
          ]
        },
        "id": "9P5gJVKRplZK",
        "outputId": "fb3fe6ab-e17c-483f-ab12-dc03b37ff3cf"
      },
      "outputs": [
        {
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'utils.datasets'",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "Cell \u001b[0;32mIn [4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39myolo_inference_util\u001b[39;00m \u001b[39mimport\u001b[39;00m run_yolo_v5\n",
            "File \u001b[0;32m~/streamlit-app/yolo_inference_util.py:16\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[39m# FILE = Path(__file__).resolve()\u001b[39;00m\n\u001b[1;32m     11\u001b[0m \u001b[39m# ROOT = FILE.parents[0]  # YOLOv5 root directory\u001b[39;00m\n\u001b[1;32m     12\u001b[0m \u001b[39m# if str(ROOT) not in sys.path:\u001b[39;00m\n\u001b[1;32m     13\u001b[0m \u001b[39m#     sys.path.append(str(ROOT))  # add ROOT to PATH\u001b[39;00m\n\u001b[1;32m     15\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mmodels\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mexperimental\u001b[39;00m \u001b[39mimport\u001b[39;00m attempt_load\n\u001b[0;32m---> 16\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mdatasets\u001b[39;00m \u001b[39mimport\u001b[39;00m LoadImages, LoadStreams\n\u001b[1;32m     17\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mgeneral\u001b[39;00m \u001b[39mimport\u001b[39;00m apply_classifier, check_img_size, check_imshow, check_requirements, check_suffix, colorstr, \\\n\u001b[1;32m     18\u001b[0m     increment_path, is_ascii, non_max_suppression, save_one_box, scale_coords, set_logging, \\\n\u001b[1;32m     19\u001b[0m     strip_optimizer, xyxy2xywh\n\u001b[1;32m     20\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mplots\u001b[39;00m \u001b[39mimport\u001b[39;00m Annotator, colors\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'utils.datasets'"
          ]
        }
      ],
      "source": [
        "from yolo_inference_util import run_yolo_v5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IbHB1E3WSX7g",
        "outputId": "b56863af-a1d0-4323-c67b-707ce868760c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/drive/My Drive/0.CV/0.Planogram_Compliance/yolov5\n"
          ]
        }
      ],
      "source": [
        "!pwd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kBz1uhGMpr1m",
        "outputId": "9d929a9e-d024-4ad0-9022-cc1dcf96f240"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "YOLOv5  2021-10-19 torch 1.9.0 CPU\n",
            "\n",
            "Fusing layers... \n",
            "Model Summary: 224 layers, 7175275 parameters, 0 gradients, 16.7 GFLOPs\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Loading data from the source ./sample_planogram.jpg\n",
            "image 1/1 f:\\2022 upwork\\plannogram_cmpliance\\yolov5\\sample_planogram.jpg: 480x640 4 Packet,F:M MAGNOLIA CHOC 1Ls, 5 Packet,FARMHOUSE FRESH MILK 1L FNDMs, 6 Packet,FARMHOUSE PLAIN LF 1Ls, 12 Packet,MAGNOLIA FRESH MILK 1L FNDMs, 3 Packet,MAG KURMA MILK 1Ls, 5 Packet,FM MAG LFHC OAT 1Ls, Done. (0.344s)\n",
            "Speed: 3.0ms pre-process, 344.0ms inference, 13.0ms NMS per image at shape (1, 3, 640, 640)\n"
          ]
        }
      ],
      "source": [
        "test_image = './sample_planogram.jpg'\n",
        "result_list = run_yolo_v5(weights='runs/train/exp5/weights/best.pt',\n",
        "    source=test_image, imgsz=[640, 640])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 180
        },
        "id": "cx4E4rBcsnEo",
        "outputId": "80e792e1-8eec-470d-d871-23a83f3c1fac"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x245a1ed3dd8>"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "test_img = cv2.imread(test_image)\n",
        "plt.imshow(test_img)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "0el6an7CsRIy"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "UsageError: Line magic function `%` not found.\n"
          ]
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "% matplotlib inline\n",
        "plt.imshow(result_list[0][0])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "veDqx048soiR",
        "outputId": "a6fbc704-d1e8-4182-b19f-85156bb3e5a3"
      },
      "outputs": [],
      "source": [
        "import json\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "import os\n",
        "import joblib\n",
        "# from .variables import old_ocr_req_cols\n",
        "# from .skew_correction import  PageSkewWraper\n",
        "\n",
        "const_HW = 1.294117647\n",
        "const_W = 600\n",
        "\n",
        "\n",
        "def bucket_sort(df, colmn, ymax_col='ymax', ymin_col='ymin'):\n",
        "    df['line_number'] = 0\n",
        "    colmn.append('line_number')\n",
        "    array_value = df[colmn].values\n",
        "    start_index = Line_counter = counter = 0\n",
        "    ymax, ymin, line_no = colmn.index(ymax_col), colmn.index(\n",
        "        ymin_col), colmn.index('line_number')\n",
        "    while counter < len(array_value):\n",
        "        current_ymax = array_value[start_index][ymax]\n",
        "        for next_index in range(start_index, len(array_value)):\n",
        "            counter += 1\n",
        "\n",
        "            next_ymin = array_value[next_index][ymin]\n",
        "            next_ymax = array_value[next_index][ymax]\n",
        "            if current_ymax > next_ymin:\n",
        "\n",
        "                array_value[next_index][line_no] = Line_counter + 1\n",
        "#                 if current_ymax < next_ymax:\n",
        "\n",
        "#                     current_ymax = next_ymax\n",
        "            else:\n",
        "                counter -= 1\n",
        "                break\n",
        "        # print(counter, len(array_value), start_index)\n",
        "        start_index = counter\n",
        "        Line_counter += 1\n",
        "    return pd.DataFrame(array_value, columns=colmn)\n",
        "\n",
        "\n",
        "def do_sorting(df):\n",
        "    df.sort_values(['ymin', 'xmin'], ascending=True, inplace=True)\n",
        "    df['idx'] = df.index\n",
        "    if 'line_number' in df.columns:\n",
        "        print('line number removed')\n",
        "        df.drop('line_number', axis=1, inplace=True)\n",
        "    req_colns = ['xmin', 'ymin', 'xmax', 'ymax', 'idx']\n",
        "    temp_df = df.copy()\n",
        "    temp = bucket_sort(temp_df.copy(), req_colns)\n",
        "    df = df.merge(temp[['idx', 'line_number']], on='idx')\n",
        "    df.sort_values(['line_number', 'xmin'], ascending=True, inplace=True)\n",
        "    df = df.reset_index(drop=True)\n",
        "    df = df.reset_index(drop=True)\n",
        "    return df\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "wgWgGkZ9sqAE"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "bb_df = pd.DataFrame(result_list[0][1].tolist(), columns =[\"xmin\",\"ymin\", \"xmax\", \"ymax\", \"conf\", \"cls\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "kZPvljQ3svQu"
      },
      "outputs": [],
      "source": [
        "sorted_df = do_sorting(bb_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zrrWTIfzsvY6",
        "outputId": "5c30a9b7-9697-4b5d-c92e-1b7a9e729497"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1.0    16\n",
              "3.0    11\n",
              "2.0     8\n",
              "Name: line_number, dtype: int64"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "sorted_df.line_number.value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MqTZ-MiKt-q8",
        "outputId": "8d7dd1da-1a24-40ed-afd7-ad8da3d8a986"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "('Packet,MAGNOLIA FRESH MILK 1L FNDM',\n",
              " 'Packet,F:M MAGNOLIA CHOC 1L',\n",
              " 'Packet,MAG KURMA MILK 1L',\n",
              " 'Packet,FM MAG LFHC OAT 1L',\n",
              " 'Packet,FARMHOUSE FRESH MILK 1L FNDM',\n",
              " 'Packet,FARMHOUSE PLAIN LF 1L')"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "names[32], names[8], names[36], names[41], names[23],   names[24]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AiOsIG_pwt4P"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LtmwjvOM0xF5",
        "outputId": "e273e557-1741-4622-b6df-9e7fa90b40f1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "master planogram\n",
            "[[         32          32          32          32          32          32          32          32          32          32          32          32           8           8           8           8]\n",
            " [         36          41          41          41          41          41          41          50          50          50          50          51          51          51          52          52]\n",
            " [         23          23          23          23          23          24          24          24          24          24          24          54          54          54          54          54]]\n"
          ]
        }
      ],
      "source": [
        "# First row\n",
        "# 32 x 12 Packet,MAGNOLIA FRESH MILK 1L FNDM\n",
        "# 8 x 4 Packet,F:M MAGNOLIA CHOC 1L\n",
        "\n",
        "# second row\n",
        "# 36 x 1 Packet,MAG KURMA MILK 1L\n",
        "# 41 x 6 Packet,FM MAG LFHC OAT 1L\n",
        "# 50 x 4\n",
        "# 51 x 3 \n",
        "# 52 x 2 \n",
        "\n",
        "# third row\n",
        "# 23 x 5 Packet,FARMHOUSE FRESH MILK 1L FNDM\n",
        "# 24 x 6 Packet,FARMHOUSE PLAIN LF 1L\n",
        "# 54 x 5\n",
        "\n",
        "n_rows = 3\n",
        "n_cols = 16\n",
        "master_table = np.zeros((n_rows, n_cols))\n",
        "# master_text_table = master_table\n",
        "#  in UI when a row number and column number is enetered \n",
        "#  give space for entering teh product anhd its count in each rows in the corerct order\n",
        "# this can be a dropdown with search feature and we do lookup from names to find the ID\n",
        "master_annotations = [[(32, 12), (8, 4)], [(36, 1), (41, 6), (50, 4), (51, 3), (52, 2)], [(23, 5), (24, 6), (54,5)]]\n",
        "# master_text_annotations = [[(32, 12), (8, 4)], [(36, 1), (41, 6), (50, 4), (51, 3), (52, 2)], [(23, 5), (24, 6), (54,5)]]\n",
        "for i, row in enumerate(master_annotations):\n",
        "    idx = 0\n",
        "    for product, count in row:\n",
        "        master_table[i, idx:idx+count] = product\n",
        "        idx = idx + count\n",
        "\n",
        "import numpy as np\n",
        "print(\"master planogram\")\n",
        "print(np.matrix(master_table))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JtrFABAV4we6",
        "outputId": "407464d3-efc7-44e5-d0a0-7d1521ef6c45"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Detected planogram\n",
            "[[         32          32          32          32          32          32          32          32          32          32          32          32           8           8           8           8]\n",
            " [         36          36          36          41          41          41          41          41         100         100         100         100         100         100         100         100]\n",
            " [         23          23          23          23          23          24          24          24          24          24          24         100         100         100         100         100]]\n"
          ]
        }
      ],
      "source": [
        "detected_table = np.zeros((n_rows, n_cols)) + 100\n",
        "for i, row  in sorted_df.groupby('line_number'):\n",
        "    # print(f\"Adding products in the row {i} to the detected planogram\", row.cls.tolist())\n",
        "    products  =row.cls.tolist()\n",
        "    detected_table[int(i-1), 0:len(products)] = products\n",
        "detected_table.shape\n",
        "print(\"Detected planogram\")\n",
        "print(np.matrix(detected_table))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QpHaRfwU5fmp",
        "outputId": "c27292a9-46d5-42b5-eeae-edae193115b1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "(master_table == detected_table).all()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FtibFVFnKg6S",
        "outputId": "7801a406-8c54-423f-f5b2-f1adfae0b7d6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.6666666666666666"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "non_null_product = 101\n",
        "(master_table == detected_table).sum() / (master_table != non_null_product).sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2s6HMMT_LYDl",
        "outputId": "2d636b1e-3855-4efe-ffb3-09a191a29e6f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.6666666666666666"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "32/ 48"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vKGn2pebPx7X",
        "outputId": "4ee46886-231e-47f2-fb3e-46b1bb82d70f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.8333333333333334"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "40/48"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mJuXqMBm5sJr",
        "outputId": "5bc31f23-b5de-4061-9058-2435172e8e49"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "(master_table == detected_table).any()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rV7iIQBRvbyd",
        "outputId": "17f22241-ce53-4e01-8f08-6a5fb8529ef0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(25, 34)"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "names.index('Packet,PURA FRESH MILK 1L FS'), names.index('Packet,MAG OMEGA PLUS PLAIN 200ML')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "hVsr63Bxs1Os",
        "outputId": "7ca4b8af-e817-432d-fbbd-21e119be13bd"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>xmin</th>\n",
              "      <th>ymin</th>\n",
              "      <th>xmax</th>\n",
              "      <th>ymax</th>\n",
              "      <th>conf</th>\n",
              "      <th>cls</th>\n",
              "      <th>idx</th>\n",
              "      <th>line_number</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>57.0</td>\n",
              "      <td>44.0</td>\n",
              "      <td>136.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>0.900506</td>\n",
              "      <td>32.0</td>\n",
              "      <td>19</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>135.0</td>\n",
              "      <td>43.0</td>\n",
              "      <td>218.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>0.903687</td>\n",
              "      <td>32.0</td>\n",
              "      <td>17</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>211.0</td>\n",
              "      <td>47.0</td>\n",
              "      <td>286.0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>0.910026</td>\n",
              "      <td>32.0</td>\n",
              "      <td>7</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>278.0</td>\n",
              "      <td>50.0</td>\n",
              "      <td>351.0</td>\n",
              "      <td>249.0</td>\n",
              "      <td>0.900455</td>\n",
              "      <td>32.0</td>\n",
              "      <td>20</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>343.0</td>\n",
              "      <td>53.0</td>\n",
              "      <td>417.0</td>\n",
              "      <td>247.0</td>\n",
              "      <td>0.909262</td>\n",
              "      <td>32.0</td>\n",
              "      <td>9</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>409.0</td>\n",
              "      <td>54.0</td>\n",
              "      <td>483.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>0.899251</td>\n",
              "      <td>32.0</td>\n",
              "      <td>21</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>475.0</td>\n",
              "      <td>55.0</td>\n",
              "      <td>548.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>0.881306</td>\n",
              "      <td>32.0</td>\n",
              "      <td>32</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>540.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>617.0</td>\n",
              "      <td>258.0</td>\n",
              "      <td>0.922429</td>\n",
              "      <td>32.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>608.0</td>\n",
              "      <td>56.0</td>\n",
              "      <td>686.0</td>\n",
              "      <td>258.0</td>\n",
              "      <td>0.908405</td>\n",
              "      <td>32.0</td>\n",
              "      <td>11</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>678.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>756.0</td>\n",
              "      <td>261.0</td>\n",
              "      <td>0.920732</td>\n",
              "      <td>32.0</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>748.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>828.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>0.921377</td>\n",
              "      <td>32.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>819.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>899.0</td>\n",
              "      <td>263.0</td>\n",
              "      <td>0.906651</td>\n",
              "      <td>32.0</td>\n",
              "      <td>14</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>887.0</td>\n",
              "      <td>57.0</td>\n",
              "      <td>971.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>0.904030</td>\n",
              "      <td>8.0</td>\n",
              "      <td>16</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>961.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>1041.0</td>\n",
              "      <td>268.0</td>\n",
              "      <td>0.897694</td>\n",
              "      <td>8.0</td>\n",
              "      <td>22</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1033.0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>1114.0</td>\n",
              "      <td>267.0</td>\n",
              "      <td>0.906937</td>\n",
              "      <td>8.0</td>\n",
              "      <td>13</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1104.0</td>\n",
              "      <td>61.0</td>\n",
              "      <td>1192.0</td>\n",
              "      <td>272.0</td>\n",
              "      <td>0.902772</td>\n",
              "      <td>8.0</td>\n",
              "      <td>18</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>87.0</td>\n",
              "      <td>306.0</td>\n",
              "      <td>159.0</td>\n",
              "      <td>504.0</td>\n",
              "      <td>0.907925</td>\n",
              "      <td>36.0</td>\n",
              "      <td>12</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>153.0</td>\n",
              "      <td>309.0</td>\n",
              "      <td>225.0</td>\n",
              "      <td>502.0</td>\n",
              "      <td>0.909513</td>\n",
              "      <td>36.0</td>\n",
              "      <td>8</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>220.0</td>\n",
              "      <td>312.0</td>\n",
              "      <td>289.0</td>\n",
              "      <td>503.0</td>\n",
              "      <td>0.905550</td>\n",
              "      <td>36.0</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>282.0</td>\n",
              "      <td>314.0</td>\n",
              "      <td>356.0</td>\n",
              "      <td>507.0</td>\n",
              "      <td>0.909124</td>\n",
              "      <td>41.0</td>\n",
              "      <td>10</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>349.0</td>\n",
              "      <td>314.0</td>\n",
              "      <td>423.0</td>\n",
              "      <td>509.0</td>\n",
              "      <td>0.912001</td>\n",
              "      <td>41.0</td>\n",
              "      <td>5</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>419.0</td>\n",
              "      <td>315.0</td>\n",
              "      <td>491.0</td>\n",
              "      <td>511.0</td>\n",
              "      <td>0.917821</td>\n",
              "      <td>41.0</td>\n",
              "      <td>3</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>482.0</td>\n",
              "      <td>317.0</td>\n",
              "      <td>555.0</td>\n",
              "      <td>514.0</td>\n",
              "      <td>0.913040</td>\n",
              "      <td>41.0</td>\n",
              "      <td>4</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>546.0</td>\n",
              "      <td>319.0</td>\n",
              "      <td>618.0</td>\n",
              "      <td>516.0</td>\n",
              "      <td>0.911265</td>\n",
              "      <td>41.0</td>\n",
              "      <td>6</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>92.0</td>\n",
              "      <td>549.0</td>\n",
              "      <td>164.0</td>\n",
              "      <td>709.0</td>\n",
              "      <td>0.889730</td>\n",
              "      <td>23.0</td>\n",
              "      <td>25</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>157.0</td>\n",
              "      <td>549.0</td>\n",
              "      <td>227.0</td>\n",
              "      <td>712.0</td>\n",
              "      <td>0.881745</td>\n",
              "      <td>23.0</td>\n",
              "      <td>31</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>219.0</td>\n",
              "      <td>552.0</td>\n",
              "      <td>289.0</td>\n",
              "      <td>715.0</td>\n",
              "      <td>0.893254</td>\n",
              "      <td>23.0</td>\n",
              "      <td>23</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>281.0</td>\n",
              "      <td>555.0</td>\n",
              "      <td>352.0</td>\n",
              "      <td>718.0</td>\n",
              "      <td>0.885784</td>\n",
              "      <td>23.0</td>\n",
              "      <td>28</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>344.0</td>\n",
              "      <td>559.0</td>\n",
              "      <td>413.0</td>\n",
              "      <td>719.0</td>\n",
              "      <td>0.880544</td>\n",
              "      <td>23.0</td>\n",
              "      <td>33</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>406.0</td>\n",
              "      <td>561.0</td>\n",
              "      <td>475.0</td>\n",
              "      <td>721.0</td>\n",
              "      <td>0.877126</td>\n",
              "      <td>24.0</td>\n",
              "      <td>34</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>467.0</td>\n",
              "      <td>562.0</td>\n",
              "      <td>537.0</td>\n",
              "      <td>724.0</td>\n",
              "      <td>0.884722</td>\n",
              "      <td>24.0</td>\n",
              "      <td>29</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>528.0</td>\n",
              "      <td>567.0</td>\n",
              "      <td>598.0</td>\n",
              "      <td>726.0</td>\n",
              "      <td>0.886900</td>\n",
              "      <td>24.0</td>\n",
              "      <td>27</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>589.0</td>\n",
              "      <td>570.0</td>\n",
              "      <td>662.0</td>\n",
              "      <td>729.0</td>\n",
              "      <td>0.890682</td>\n",
              "      <td>24.0</td>\n",
              "      <td>24</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>653.0</td>\n",
              "      <td>573.0</td>\n",
              "      <td>726.0</td>\n",
              "      <td>734.0</td>\n",
              "      <td>0.887247</td>\n",
              "      <td>24.0</td>\n",
              "      <td>26</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>717.0</td>\n",
              "      <td>575.0</td>\n",
              "      <td>793.0</td>\n",
              "      <td>738.0</td>\n",
              "      <td>0.884721</td>\n",
              "      <td>24.0</td>\n",
              "      <td>30</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      xmin   ymin    xmax   ymax      conf   cls  idx  line_number\n",
              "0     57.0   44.0   136.0  246.0  0.900506  32.0   19          1.0\n",
              "1    135.0   43.0   218.0  246.0  0.903687  32.0   17          1.0\n",
              "2    211.0   47.0   286.0  246.0  0.910026  32.0    7          1.0\n",
              "3    278.0   50.0   351.0  249.0  0.900455  32.0   20          1.0\n",
              "4    343.0   53.0   417.0  247.0  0.909262  32.0    9          1.0\n",
              "5    409.0   54.0   483.0  242.0  0.899251  32.0   21          1.0\n",
              "6    475.0   55.0   548.0  255.0  0.881306  32.0   32          1.0\n",
              "7    540.0   56.0   617.0  258.0  0.922429  32.0    0          1.0\n",
              "8    608.0   56.0   686.0  258.0  0.908405  32.0   11          1.0\n",
              "9    678.0   57.0   756.0  261.0  0.920732  32.0    2          1.0\n",
              "10   748.0   57.0   828.0  263.0  0.921377  32.0    1          1.0\n",
              "11   819.0   57.0   899.0  263.0  0.906651  32.0   14          1.0\n",
              "12   887.0   57.0   971.0  267.0  0.904030   8.0   16          1.0\n",
              "13   961.0   59.0  1041.0  268.0  0.897694   8.0   22          1.0\n",
              "14  1033.0   59.0  1114.0  267.0  0.906937   8.0   13          1.0\n",
              "15  1104.0   61.0  1192.0  272.0  0.902772   8.0   18          1.0\n",
              "16    87.0  306.0   159.0  504.0  0.907925  36.0   12          2.0\n",
              "17   153.0  309.0   225.0  502.0  0.909513  36.0    8          2.0\n",
              "18   220.0  312.0   289.0  503.0  0.905550  36.0   15          2.0\n",
              "19   282.0  314.0   356.0  507.0  0.909124  41.0   10          2.0\n",
              "20   349.0  314.0   423.0  509.0  0.912001  41.0    5          2.0\n",
              "21   419.0  315.0   491.0  511.0  0.917821  41.0    3          2.0\n",
              "22   482.0  317.0   555.0  514.0  0.913040  41.0    4          2.0\n",
              "23   546.0  319.0   618.0  516.0  0.911265  41.0    6          2.0\n",
              "24    92.0  549.0   164.0  709.0  0.889730  23.0   25          3.0\n",
              "25   157.0  549.0   227.0  712.0  0.881745  23.0   31          3.0\n",
              "26   219.0  552.0   289.0  715.0  0.893254  23.0   23          3.0\n",
              "27   281.0  555.0   352.0  718.0  0.885784  23.0   28          3.0\n",
              "28   344.0  559.0   413.0  719.0  0.880544  23.0   33          3.0\n",
              "29   406.0  561.0   475.0  721.0  0.877126  24.0   34          3.0\n",
              "30   467.0  562.0   537.0  724.0  0.884722  24.0   29          3.0\n",
              "31   528.0  567.0   598.0  726.0  0.886900  24.0   27          3.0\n",
              "32   589.0  570.0   662.0  729.0  0.890682  24.0   24          3.0\n",
              "33   653.0  573.0   726.0  734.0  0.887247  24.0   26          3.0\n",
              "34   717.0  575.0   793.0  738.0  0.884721  24.0   30          3.0"
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